Generative AI Use Case Library for the Technology Service Provider Industry
Identify value-driven AI use cases to transform your organization.
- Your customers are seeking a knowledgeable, trusted partner. You need to provide support for unproven technology, and if you can’t intelligently discuss the topic, the business will land elsewhere.
- You need to master your own use of Gen AI to develop expertise, drive innovation, and remain competitive. You need to develop capacity and credibility.
- You need to prioritize and focus resources. You need to identify high-value applications that will successfully translate into meaningful returns on investment.
Our Advice
Critical Insight
Technology service providers should approach AI adoption, internally and with clients, strategically and responsibly. A clear understanding of the specific use cases and their benefits is needed alongside a plan for addressing the challenges associated with implementation and ongoing use. Technology service providers can take on a risk-based approach to act on sophisticated AI technology and ready-to-use solutions to balance AI opportunities and risks.
Impact and Result
- Quickly brainstorm opportunities to deploy Gen AI technology internally and with clients.
- Align use cases with specific business capabilities and adopt a capability-centric mindset.
- Prepare to launch your Gen AI proof-of-concept project.
Generative AI Use Case Library for the Technology Service Provider Industry
Identify value-driven AI use cases to transform your organization.
Analyst Perspective
Deploy value-driven artificial intelligence (AI) use cases aligned with core capabilities.
Customers are calling about Generative AI (Gen AI), and the urgency to adopt the technology as soon as possible is ringing loud and clear. Right or wrong, businesses are genuinely concerned that failing to adopt this transformative technology could make them irrelevant in the coming year. They are under pressure from boards to transform the hype into action and they need help from a trusted partner.
Meanwhile, technology service providers are challenged on multiple fronts. Internally, they need to adopt AI technology to improve their operations, reassure their employees about coming change, and develop critical skill sets to successfully execute on future projects. Externally, they need to provide thought leadership to clients, develop intellectual property for resale, and confidently advise on navigating uncertain risk. These are not trivial undertakings and require careful consideration.
Success with Gen AI and AI is not just about understanding the current state but also about learning to consider future possibilities. To support our members in this complex endeavor, we have curated a list of ideas and resources. Categorized into eight business capability themes, we've included a range of use case ideas, business scenarios, case studies, and a selection of insightful videos from our growing library. These can be used as conversation starters, both internally and externally.
The best AI use cases will come from rich discussions with stakeholders. Our use case library provides content to initiate conversations, and our primary aim is to help you kick off brainstorming with a practical starting point for developing future ideas.
Justin St-Maurice, PhD
Principal Research Director
Technology Service Providers
Info-Tech Research Group
Executive Summary
| Your Challenge | Common Obstacles | Info-Tech's Approach |
| Your customers are seeking a knowledgeable, trusted partner. You must provide support for unproven technology, and if you can't intelligently discuss the topic, the business will land elsewhere.
You must master your own use of Gen AI to develop expertise, drive innovation, and remain competitive. You must develop capacity and credibility. You must prioritize and focus resources. You must identify low complexity, high value applications that will successfully translate into meaningful returns on investment (ROIs). |
Key stakeholders have a limited understanding of the technology and unrealistic expectations about outcomes and their alignment with strategic objectives.
Risk implications are poorly defined. Unknown costs, new legislative frameworks, and pending case law create an environment of uncertainty. Practical use cases for Gen AI remain unclear, and you're unsure what possibilities to explore first. You can't determine ROI before understanding the application, impacts, and costs. |
Introduce an approach to building your Gen AI roadmap rapidly and responsibly via a six-step practical framework to accelerate the adoption.
Help business leaders and clients understand and discover AI use cases that can–address some of their business challenges while supporting organizational strategic goals. Guide business and IT leaders to start their AI journey by identifying and prioritizing–AI use cases for their–business capabilities through a benefits realization model. |
Info-Tech Insight
Technology service providers should approach–AI adoption strategically and responsibly, whether internally or with clients. A clear understanding of the specific use cases and their benefits is needed alongside a plan–for addressing the challenges–associated–with implementation and ongoing use.–Technology service providers can adopt a risk-based approach to act on sophisticated AI technology and ready-to-use solutions to balance AI opportunities and risks.
Generative AI is an innovation in machine learning
Generative AI (Gen AI)
A form of machine learning where, in response to prompts, a Gen AI platform can generate new outputs based on the data it has been trained on. Depending on its foundational model, a Gen AI platform will provide different modalities and thereby use case applications.
Audio – Converts text to sound
Visual – Enables text to image, video, or web design conversions
Code – Creates code in various programming languages based on human language prompts
Text – Creates text-based outputs such as articles, blog posts, emails, and information summaries
Machine learning (ML)
An approach to implementing AI where the AI system is instructed to search for patterns in a data set and then make predictions based on that set. In this way, the system "learns" to provide accurate content over time (e.g. Google's search recommendations).
Artificial intelligence (AI)
A field of computer science that focuses on building systems to imitate human behavior. Not all AI systems have learning behavior – many systems, such as customer service chatbots, operate on preset rules.
Info-Tech Insight
Many vendors have jumped on Gen AI as the latest marketing buzzword. When vendors proclaim to offer Gen AI functionality, pin down what exactly is generative about it. The solution must be able to induce new outputs from inputted data via self-supervision – not just trained to produce certain outputs based on certain inputs.
Gen AI is catalyzing AI adoption
Gen AI technology has gained significant attention due to its ease of public access. Two months after launch, ChatGPT was estimated to have reached 100 million monthly active users (Reuters, 2023).
Organizations are rushing to create their first AI strategies (Scale, 2023) and consultant networks are reporting that Gen AI is the number one reason for client intake calls. Organizations everywhere are nervous and want to avoid losing an opportunity for competitive advantage.
Gen AI is seen as an opportunity to enhance existing capabilities and improve efficiency but can also deliver novel outcomes that wouldn't otherwise be possible. Creativity and innovation must be tempered by pragmatism.
65% of global organizations have created their first AI strategy or accelerated their existing AI strategies in 2023 (Scale, 2023).
Let the AI ecosystem drive value
Gen AI and large language models (LLMs) are tools in a much larger toolbox that can be used to drive enhancements to capabilities. Gen AI is part of a rich AI ecosystem, and technology service providers should consider a wide range of AI capabilities to drive strategy to help themselves and their clients.
Existing AI technologies have reached maturity beyond the current capability of Gen AI across industries around the globe. For example, robotic process automation (RPA) and intelligent automation (IA) are well understood – each has mature platforms, tangible returns on investment, and low barriers to entry. Technology service providers should consider how these –legacy' AI solutions are complemented, rather than supplanted, by Gen AI.
Source: McKinsey & Company, 2022
The benefits of Gen AI can't be realized in isolation and require organizational support, investment, and discipline in the areas of information management, big data, and risk assessment. Organizations that can fully unlock the value of data will be in great shape for AI adoption.
Gen AI objectives and the larger AI strategy must align with specific business goals; they should not be done for the sake of doing them. If AI initiatives have specific outcomes in mind, technology service providers and their clients can improve customer experience through automation, personalize and target services, streamline responses times, and increase operational efficiency. Driving additional types of value will be a source of intellectual property.
Source: Scale, 2023
Understand the opportunities and risks of Gen AI
Gen AI is a transformative opportunity for technology service providers and their clients.
Gen AI driven process enhancement, content creation, and analytics can significantly enhance business performance.
Workforce augmentation
Gen AI optimizes task efficiency and augments skill sets. By enhancing productivity, it helps secure and expand market share and boost competitive advantage.
Idea generation
Gen AI quickly supports in-depth brainstorming and creativity by suggesting alternate ideas and potential options. It fosters innovative strategies alongside users to generate unique solutions and ideas.
Data analysis and insights
Gen AI can provide analysis of structured and unstructured data, understand nuanced meaning, and provide deep data analysis to reveal key market insights. Gen AI delivers new types of market insight.
Gen AI is not risk-free and important questions remain unanswered.
As the EU AI Act includes energy consumption as part of the framework to regulate AI, legislative and environmental issues are just starting to become clear (Stanford, 2023). Meanwhile, future licensing costs are a known unknown that must be incorporated into risk management decisions.
Case law and legislation
The use of copywritten materials to train LLMs is untested in court (New York Times, 2023). Meanwhile, countries around the world are developing new legislation to control the use of AI (WEF, 2023).
Future operating costs
ChatGPT 3 costs around $700,000 per day to operate, with OpenAI operating at a $540M loss in 2022 (Insider, 2023). Assuming vendors will one day be profitable, organizations must anticipate the true cost of Gen AI technologies as they mature.
Environmental Impacts
The energy to train a model can power the average American home for 41 years (Luccioni et al, 2023) and ChatGPT consumes a bottle of water for every 20 to 50 questions it is asked (Euronews.green, 2023).
Info-Tech Insight
Technology service providers should consider the evolving legal landscape, potential future licensing costs, and environmental issues as pillars of strategy when assessing the value, impacts, and risks of Gen AI.
Info-Tech's approach and team can help, irrespective of where you are in your digital journey
| Starting | Benefiting | ||||
| Where are you in the journey? | Establish your digital North Star | Quantify the value of digital use cases | Create the digital roadmap | Deliver digital use cases and realize impact | Create the infrastructure to drive and sustain change |
| Set aspiration: Vision setting with key business unit stakeholders to discuss and align on digital aspiration (e.g. Big-T vs. Mini-T, self-funded and slow burn vs. investments) | Assess opportunity: Comprehensive enterprise-to-enterprise (E2E) understanding of the digital opportunity across business units (BUs)/functions (e.g. data analysis, process walks, and interviews) | Design and plan: Bottom-up–initiative design and planning (e.g.–opportunity to initiatives,–financials, phasing, design–principles) | Execute: Detailed initiative builds and implementation, execution with rigor and transparency (e.g. process optimization then automation, test, measure, scale) | Enable: Set up the transformation infrastructure, operating model, and culture to drive value capture and sustain change. | |
| Examples of how Info-Tech can help | Digital North Star placement (e.g. industry trends, top-down opportunity, high-level planning) |
Digital maturity assessments (e.g. current-state digital adoption and transformation readiness) |
Initiative bottom-up design (e.g. initiative ideation and business case creation, workplan, investments) |
Initiative build (e.g. zero-based process redesign with technology) |
Transformation infrastructure (e.g. transformation program design, transformation office) |
| Opportunity assessments* (e.g. BU/function value creation diagnostics, opportunity levers) |
Holistic initiative planning (e.g. phasing, interdependencies, investments) |
Initiative implementation (e.g. testing and pilot, scale up roadmap, performance tracking) |
IT modernization (e.g. technology infrastructure required to execute digital levers) |
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| Value assurance assessment (e.g. course correcting and accelerating initiatives underway) |
Change management (e.g. org-wide change program and stories, comms, governance) |
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| Performance management (e.g. KPIs – leading and lagging, people mgmt. for continuous imp.) |
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| Workforce management (e.g. upskilling, right people, right place, right time) |
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*Applicable framework element for this document
The following content will provide an overview of Gen AI/AI/ML use cases in the technology service provider industry. This will support opportunity assessments across the organization's value chain. Note: This does not provide the value/ROI specific to your organization. To do that, detailed current-state assessments and opportunity assessments must be executed.
Measure the value of this document
Document your objective
Highlight best-in-class use cases to spur the initiative-planning and ideation process.
Measure your success against that objective
There are multiple qualitative and quantitative, direct and indirect metrics by which you can measure the progress of your initiative pipeline's development. Some examples are:
- Increased initiative pipeline value
- Number of capabilities impacted by initiative pipeline
- Enhanced understanding of the initiatives' impact aligned to the organization's capability map
- Better understanding of which sources of value are being addressed or under-addressed in the organization's initiative pipeline
See Establish Your Digital Transformation Governance in the Digital Transformation Center for more details
Gen AI Use Case Library Methodology
SECTION 1
What is a Gen AI use case?
A Gen AI use case is a technology or combination of technologies applied to a specific capability (e.g. job to be done) within a given industry/function to create value.
Use case
Capabilities
The activities, or jobs to be done, that your organization performs to ultimately deliver a product/service.
Technology
The base technology that enables value-creating performance gains.
Industry or function
The relevant industry or function (many use cases will apply across multiple industries/functions).
The Gen AI use case library
What is it?
A use case represents a technology or combination of technologies applied to a capability within a given industry or function that drives value. The Gen AI use case library is a non-exhaustive list of Gen AI/AI/ML use cases that can be organized by industry/function, capability, or technology. The organizing principle in this document is by industry/function.
Why is it important?
In the context of a digital transformation, the Gen AI/AI/ML use case library:
- Identifies potential sources of value to analyze in a top-down opportunity assessment.–
- Jumpstarts the idea generation process during the initiative development phase. Use cases are the foundational building blocks of the initiatives that ultimately deliver value to the business.
Gen AI use case library
Leverage best-in-class digital use cases to build strong implementation roadmaps and maximize value creation
Gen AI use case
A technology or combination of technologies applied to a specific capability within a given industry or function to create value.
What is a use case?
Industry or function
The relevant industry or function a use case applies to (many use cases will apply across multiple industries/functions).
Capability
The activities, or "jobs to be done," that your organization performs to ultimately deliver a product/service.
Technology
The base Gen AI/AI/ML technology that a use case leverages to enable value-creating performance gains.
What is covered with each use case?
Capability category mapping
Identification of a specific business capability from the business reference architecture.
Business need
A description of the business need within the capability category.
Use case details
A high-level, conceptual description of the use case and how it would fit into existing workflows and business functions.
Business benefits
A description of the benefits of implementing the use case. This provides insights into the value proposition.
Source of value mapping
A mapping between the use case and the business sources of value. This identifies the impacted value creation areas.
Leverage the technology service provider industry capability map to identify candidate opportunities/initiatives
Business capability map defined–
In business architecture, the primary view of an organization is known as a business capability map.
Business capability defines what a business does to enable value creation, rather than how. Business capabilities:
- Represent stable business functions.
- Are unique and independent of each other.
- Typically, will have a defined business outcome.
Technology Services Capabilities Tree
Value streams
Core components of an organization's value chain or support structure.
Level 1: Capabilities
The top-level activities that an organization performs to ultimately deliver a product or service.
Level 2: Sub-capabilities
The sub-activities, or jobs to be done, performed within an overarching capability.
Download the Technology Service Provider Industry Business Reference Architecture Template
Use cases apply to a specific Level 1 or Level 2 capability.
AI use cases support technology service strategy from sources of value
Sources of value
Operational efficiency
Reducing costs through operational performance improvements.
Customer experience
Improving the customer experience with a product/service via reliability, engagement, transparency, etc.
Business growth
Expanding the organization's products/services/capabilities to ultimately drive revenue expansion or customer impact.
Employee experience
Optimizing the employee experience through changes that make work easier and more enjoyable thus increasing job satisfaction.
Risk and resilience
Mitigating diverse risk, health, safety, and continuity of operations concerns to preserve stable and sustainable performance.
Environmental, social, and governance (ESG)
Improving environmental impacts, social and community wellbeing, and corporate governance practices.
Use Cases for the Technology Service Provider Industry
SECTION 2
Use case library overview
Top use case categories by priority business capabilities
MEMBER SURVEY RESULTS
Business Development Use Cases
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